Lead research projects that apply formal methods, program analysis, automated reasoning, and AI-driven techniques (including code generation and modeling) to real problems in our cloud data platform.
Translate research ideas into prototypes, then into shipped capabilities that move concrete business metrics — quality, velocity, reliability, and operational performance at scale.
Partner closely with engineering leaders, product managers, and key customers to identify high-leverage opportunities and turn them into deliverables.
Influence the engineering and product roadmap; advise leaders on which research directions are pragmatic and which are not.
Train and uplevel engineering teams on new methods, and scale those methods across the organization.
Maintain expertise at the frontier of the field through publications, conference participation, open-source contributions, and patent filings.
Qualification
Formal methods — eDistributed systems — designingComfortable in a fast-pacedAbout working here
Required
PhD (or equivalent research experience) in Computer Science or a closely related field.
Depth across the areas this role sits at the intersection of:
Formal methods — e.g., model checking, theorem proving, SAT/SMT, program verification, type systems, or program analysis.
Distributed systems — designing, reasoning about, or verifying large-scale concurrent and distributed systems.
Software engineering — strong fundamentals; able to go from a research idea to production-quality code in collaboration with engineering teams.
AI / ML — practical experience applying modern ML, including LLMs, to systems problems such as code generation, synthesis, or automated reasoning.
8+ years applying theoretical computer science to large-scale software systems — ideally cloud data platforms, distributed systems, or developer infrastructure.
Demonstrated ability to drive company-level initiatives in partnership with engineering and product leadership. (Weighted more heavily for Principal-level candidates.)
Track record of technical contribution to the field — publications, open-source work, patents, or comparable evidence of impact.
Comfortable in a fast-paced, ambiguous environment where impact is measured by what ships.
About working here
Every Snowflake employee is expected to follow the company's confidentiality and security standards for handling sensitive data, and to keep customer information secure and confidential as an essential part of their duties.
